Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common complex orofacial birth defect associated with significant morbidity and increased mortality. Surgical correction is always required and the multidisciplinary health interventions cost approximately a half billion dollars each year. Candidate gene studies and GWAS have identified a number of putative NSCLP genes and loci that are estimated to account for only ~20% of the genetic variation. While this represents an important starting point, the majority of genetic risk for NSCLP remains undiscovered and represents a frontier to be explored. We have used both candidate gene and GWAS approaches to define genetic variation in NSCLP; a previously unsuspected gene, CRISPLD2, was found to be associated with NSCLP and, when knocked down in zebrafish, causes palatal and jaw abnormalities. The goal of this project is to continue identifying and understanding the undiscovered variation that contributes to the genetic architecture of NSCLP. To accomplish this goal, we will apply the newest technologies, whole exome next generation sequencing (WES) and chromosomal microarray analysis (CMA) to our well-characterized extensive family-based NSCLP dataset. We will use the WES that detects coding and noncoding variants (Agilent 50Mb v.4 exon content +UTR) because we have shown that both types of variation contribute to NSCLP. In addition, CMA will detect copy number variants (CNVs) that would be missed by WES. This will provide the most complete coverage and the family-based design will allow for detection familial causes of NSCLP. Candidate genes will be prioritized, functionally tested in zebrafish to determine biological significance and analyzed in our case controls for spectrum variation and risk modeling. The results will provide important information about risk variants, individually and in aggregate. During the entire study period, we will continue to expand our NSCLP dataset for this and future genetic studies. Application of the newest technology to our extensive family-based dataset is a powerful method for uncovering the genetic variation contributing to this common birth defect. This approach is a significant step forward; the results will add important new information to the developing knowledge base of genetic variation responsible for NSCLP, which will translate into genetic counseling for at-risk families.